Three new approaches for the analysis of ventricular repolarisation in 12-lead electrocardiograms (ECGs) are presented: the spatial and temporal variations in T-wave morphology and the wavefront direction difference between the ventricular depolarisation and repolarisation waves. The spatial variation characterises the morphology differences between standard leads. The temporal variation measures the change in interlead relationships. A minimum dimensional space, constructed by ECG singular value decomposition, is used. All descriptors are measured using the ECG vector in the constructed space and the singular vectors that define this space. None of the descriptors requires time domain measurements (e.g. the precise detection of the T-wave offset), and so the inaccuracies associated with conventional QT interval related parameters are avoided. The new descriptors are compared with the conventional measurements provided by a commercial system for an automatic evaluation of QT interval and QT dispersion in digitally recorded 12-lead ECGs. The basic comparison uses a set of 1100 normal ECGs. The short-term intrasubject reproducibility of the new descriptors is compared with that of the conventional measurements in a set of 760 ECGs recorded in 76 normal subjects and a set of 630 ECGs recorded in 63 patients with hypertrophic cardiomyopathy (ten serial recordings in each subject of both these sets). The discriminative power of the new and conventional parameters to distinguish normal and abnormal repolarisation patterns is compared using the same set. The results show that the new parameters do not correlate with the conventional QT interval-related descriptors (i.e. they assess different ECG qualities), are generally more reproducible than the conventional parameters, and lead to a more significant separation between normal and abnormal ECGs, both univariately and in multivariate regression models.

Spatial heterogeneity of ventricular repolarization exists and is measurable in 12-lead resting ECGs. It differs between different clinical groups, but the so-called QT dispersion is unrelated to it.

The study investigated interobserver and intrasubject reproducibility of QT interval duration and dispersion measured in standard 12-lead ECGs recorded at 25 mm/sec. Twenty-eight healthy volunteers were studied. Each underwent four ECG recordings, which were performed 1, 7, and 30 days apart. Two independent observers analyzed each ECG record. In each lead with a distinguishable T wave pattern, the RR interval, Q-peak of T interval, and Q-end of T interval were measured using a digitizing board with a 0.1-mm resolution. From each recording the following measures were derived: the maximum, minimum, and mean QT interval; maximum, minimum, and mean heart rate corrected QT interval (QTc); QT and QTc dispersion (the difference between the maximum and minimum QT interval among the 12 leads); and adjusted QT and QTc dispersion (dispersion divided by the square root of the number of leads measured). The interobserver and short-term (1 day) and long-term (1 week and 1 month) reproducibility of individual indices was assessed by computing the relative errors and comparing them by a standard sign test. In addition, the distributions of maximum and minimum QTc values among electrocardiographic leads, and the differences between QT-end and QT-peak based measurements were investigated. The results showed that: (1) the measurement of the QT interval from standard ECG recordings is feasible and not operator dependent (interobserver relative error < 4%); (2) the duration of the QT interval in healthy volunteers is stable and its short- and long-term reproducibility is high (intrasubject relative error < 6%); (3) parameters that characterize dispersion of the QT interval in the 12-lead ECG are highly nonreproducible, both between subsequent recording (relative error of 25%-35%) and between observers (relative error 28%-33%), the reproducibility of QT dispersion is significantly lower than that of QT duration (P < 0.01); and (4) the duration of the entire QT interval correlates only weakly with the duration of the Q-peak of T interval.

Patients with dilated cardiomyopathy commonly have an affected family member and a high proportion of apparently healthy relatives with minor echocardiographic abnormalities. Segregation analysis suggests that familial dilated cardiomyopathy is the result of the transmission of a rare autosomal dominant gene. Further studies are currently underway to characterise the molecular basis of familial dilated cardiomyopathy and identify early disease within these families.

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The costs of clinical investigations of drug-induced QT interval prolongation are mainly related to manual processing of electrocardiographic (ECG) recordings. Potentially, however, these costs can be decreased by automatic ECG measurement. To investigate the improvements in measurement accuracy of the modern ECG equipment, this study investigated QT interval measurement by the "old" and "new" versions of the 12SL ECG algorithm by GE Healthcare (Milwaukee, WI, USA) and compared the results to carefully validated and reconciled manual measurements. The investigation used two sets (A and B) of ECG recordings that originated from large clinical studies. Sets A and B consisted of 15,194, and 29,866 10-second ECG recordings, respectively. All the recordings were obtained with GE Healthcare recorders and were available in digital format compatible with ECG processing software by GE Healthcare. The two sets of recordings differed significantly in ECG quality with set B being substantially more noise polluted. Compared to careful manual QT interval readings in recording set A, the errors of the automatic QT interval measurement were (mean +/- SD) +3.95 +/- 5.50 ms, and +0.51 +/- 12.41 ms for the "new" and "old" 12SL algorithm, respectively. In recording set B, these numbers were +2.41 +/- 9.47 ms, and -0.17 +/- 14.89 ms, respectively (both differences were highly statistically significant, P < 0.000001). In recording set A, 95.9% and 76.6% of ECGs were measured automatically within 10 ms of the manual measurement by the "new" and "old" versions of the 12SL algorithm, In recording set B, these numbers were 83.9% and 59.5%. The errors made by the "new" and "old" version of 12SL algorithm were practically independent each of the other (correlation coefficients of 0.031 and 0.281 in recording sets A and B, respectively). The study shows that (a) compared to the "old" version of the 12SL algorithm, the QT interval measurement by the "new" version implemented in the most recent ECG equipment by GE Healthcare is significantly better, and (b) the precision of automatic measurement by the 12SL algorithm is substantially dependent on the quality of processed ECG recordings. The improved accuracy of the "new" 12SL algorithm makes it feasible to use modern ECG equipment without any manual intervention in selected parts of drug-development program.

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